In the NAS community, the search space represents the space where we search the DNN's architecture. Thanks to a set of operations and a backbone explaining how operations can be connected to construct valid network architectures, it is defined thanks to a set of operations and a backbone.
The search space can be classified into two categories. The first one is the
Global Search Space where the algorithm has to learn all the DNN architecture.
The second one is the Cell-Based Search Space where the DNN architecture lies in a backbone composed of basic components
called cells, and the goal is to learn what is inside the cells.
Inspired by DNN architecture such as ResNet [1]}, VGG [2]}, and Inception [3]}, the author of NASNET [4]}, who initially proposed cell-based search space, noticed that a DNNs are composed of blocks with the same kind of operations that are repeated multiple times. In Figure REF , we represented the backbone of DNN model for CIFAR10 [5]}.
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